Ponencia
A Comparison of classification/regression trees and logistic regression in failure models
Autor/es | Irimia Diéguez, Ana Isabel
Blanco Oliver, Antonio Jesús Vázquez Cueto, María José |
Departamento | Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones |
Fecha de publicación | 2015 |
Fecha de depósito | 2018-12-17 |
Publicado en |
|
Resumen | The use of non-parametric statistical methods, the development of models geared towards the homogeneous characteristics of
corporate sub-populations, and the introduction of non-financial variables, are three main issues ... The use of non-parametric statistical methods, the development of models geared towards the homogeneous characteristics of corporate sub-populations, and the introduction of non-financial variables, are three main issues analysed in this paper. This study compares the predictive performance of a non-parametric methodology, namelyClassification/Regression Trees (CART), against traditional logistic regression (LR) by employing a vast set of matched-pair accounts of the smallest enterprises, known as micro-entities,from the United Kingdom for the period 1999 to 2008 that includes financial, non-financial, and macroeconomic variables. Our findings show that CART outperforms the standard approach in the literature, LR. |
Cita | Irimia Diéguez, A.I., Blanco Oliver, A.J. y Vázquez Cueto, M.J. (2015). A Comparison of classification/regression trees and logistic regression in failure models. En Global conference on business, economics, management and tourism (2ª. 2014. Praga), Praga. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
A comparison.pdf | 257.0Kb | [PDF] | Ver/ | |